IP Library › Granted Patent US 12,229,886
Granted Patent B2
US 12,229,886 · App. 17/491,794 · Granted Feb 18, 2025

Historical crop state model, predictive crop state map generation and control system

Inventors: Noel W. Anderson (Fargo, ND); Eric M. Heien (Davis, CA); Nathan R. Vandike (Geneseo, IL)
Assignee: Deere & Company
G06T17/05A01B79/005G05D1/0212G06T7/70G06V20/188G06T2207/30188G06T2215/12
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Quick Facts
Patent No.
US 12,229,886
App. No.
17/491,794
Granted
Feb 18, 2025
Kind
B2
Abstract

Historical and seasonal data is obtained by an agricultural work machine. The historical data provides historical values of agricultural characteristics, which may or may not be geolocated, and the seasonal data provides seasonal values of agricultural characteristics corresponding to a current season. A predictive map generator generates a predictive map that predicts an agricultural characteristic, such as crop state, at different locations in the field based on a relationship between the historical values of agricultural characteristics in the historical data and based on the seasonal values of agricultural characteristics in the seasonal data at those different locations. The predictive map can be output and used in automated machine control.

Claims (67)

1. An agricultural system comprising

a communication system configured to obtain:

historical crop state data indicative of historical values of crop state;

historical agricultural characteristic data indicative of historical values of an agricultural characteristic; and

seasonal data indicative of geolocated seasonal values of the agricultural characteristic corresponding to a current season; and

a predictive map generator configured to generate a functional predictive crop state map of a field to be harvested by an agricultural work machine that maps predictive crop state values to different geographic locations in the field to be harvested based on the historical values of crop state and the historical values of the agricultural characteristic and based on the seasonal values of the agricultural characteristic at those different geographic locations;

a geographic position sensor configured to detect a geographic location of the agricultural work machine; and

a control system configured to generate a control signal to control a controllable subsystem of the agricultural work machine based on a detected geographic location of the agricultural work machine and based on the functional predictive crop state map.

2. The agricultural system of claim 1 , wherein the predictive crop state values indicate one or more of a magnitude of crop lodging of the crop at the field or an orientation of the crop at the field.

3. The agricultural system of claim 1 and further comprising:

a predictive model generator configured to generate a historical predictive crop state model that models a relationship between the historical values of crop state and the historical values of the agricultural characteristic, wherein the predictive map generator is configured to generate the functional predictive crop state map based on the seasonal values of agricultural characteristic in the seasonal data and based on the historical predictive crop state model.

4. The agricultural system of claim 1 , wherein the historical values of the agricultural characteristic comprise historical crop planting values and wherein the seasonal values of the agricultural characteristic comprise seasonal crop planting values.

5. The agricultural system of claim 1 , wherein the historical values of the agricultural characteristic comprise historical weather values and wherein the seasonal values of the agricultural characteristic comprise seasonal weather values.

6. The agricultural system of claim 1 , wherein the historical values of the agricultural characteristic comprise historical crop development values and wherein the seasonal values of the agricultural characteristic comprise seasonal crop development values.

7. The agricultural system of claim 1 , wherein the historical crop state data indicative of historical values of crop state comprises one or more of historical harvesting data and or historical in-situ sensor data indicative of historical detected values of crop state.

8. The agricultural system of claim 1 , and further comprising:

an in-situ sensor configured to detect a value of crop state corresponding to a geographic location in the field; and

wherein the predictive map generator is configured to generate a revised functional predictive crop state map of the field that maps revised predictive crop state values to different geographic locations in the field based on the detected value of crop state.

9. The agricultural system of claim 1 and further comprising:

a predictive model generator configured to generate a revised historical predictive crop state model that models a relationship between crop state values, which include a crop state value detected in-situ during a current operation and the historical values of crop state, and agricultural characteristic values, which include the historical values of the agricultural characteristic and a seasonal value of the agricultural characteristic corresponding to a location of the crop state value, wherein the predictive map generator is configured to generate a revised functional predictive crop state map of the field that maps revised predictive crop state values to different geographic locations in the field based on the seasonal values of the agricultural characteristic in the seasonal data at those different geographic locations and based on the revised historical predictive crop state model.

10. The agricultural system of claim 1 , wherein the control system comprises at least one of:

a header/reel controller configured to generate a header control signal based on the detected geographic location of the agricultural work machine and the functional predictive crop state map and control the controllable subsystem based on the header control signal to control a height, tilt, or roll of a header of the agricultural work machine or a reel position of a reel of the agricultural work machine;

a settings controller configured to generate a speed control signal based on the detected geographic location of the agricultural work machine and the functional predictive crop state map and control the controllable subsystem based on the speed control signal to control a speed of the agricultural work machine;

a path planning controller configured to generate a path planning control signal, indicative of a route, based on the detected geographic location of the agricultural work machine and the functional predictive crop state map and control the controllable subsystem based on the route; or

an operator interface controller configured to generate an operator interface control signal to control the controllable subsystem to generate a user interface map representation of the functional predictive crop state map.

11. A computer implemented method of controlling an agricultural work machine, the computer implemented method comprising:

obtaining historical crop state data indicative of historical values of crop state;

obtaining historical agricultural characteristics data indicative of historical values of agricultural characteristics;

obtaining seasonal data indicative of geolocated seasonal values of the agricultural characteristics corresponding to a current season;

generating a functional predictive crop state map of a field that maps predictive crop state values to different geographic locations in the field based on the historical values of crop state and the historical values of the agricultural characteristics and based on the seasonal values of the agricultural characteristics at those different geographic locations;

detecting a geographic location of the agricultural work machine;

controlling a controllable subsystem based on the geographic location of the agricultural work machine and based on the functional predictive crop state map.

12. The computer implemented method of claim 11 and further comprising:

generating a historical predictive crop state model that models a relationship between the historical values of crop state and the historical values of the agricultural characteristics, wherein generating the functional predictive crop state map comprises generating the functional predictive crop state map based on the seasonal values of the agricultural characteristics in the seasonal data and based on the historical predictive crop state model.

13. The computer implemented method of claim 11 and further comprising:

detecting, with an in-situ sensor, an in-situ value of crop state corresponding to a geographic location on the field.

14. The computer implemented method of claim 13 and further comprising:

generating a revised functional predictive crop state map of the field that maps revised predictive crop state values to different geographic locations in the field based on the detected in-situ value of crop state.

15. The computer implemented method of claim 14 and further comprising:

generating a revised historical predictive crop state model that models a relationship between crop state values, which include the in-situ value of crop state and the historical values of crop state, and agricultural characteristics values, which include the historical values of the agricultural characteristics and the seasonal values of the agricultural characteristics corresponding to the geographic location of the in-situ value of crop state, wherein generating the revised functional predictive crop state map comprises generating the revised functional predictive crop state map based on the seasonal values of the agricultural characteristics in the seasonal data and based on the revised historical predictive crop state model.

16. The computer implemented method of claim 11 , wherein obtaining historical agricultural characteristics data that includes historical values of the agricultural characteristics comprises one or more of:

obtaining historical crop planting data that includes historical crop planting values;

obtaining historical weather data that includes historical weather values; or

obtaining historical crop development data that includes historical crop development values.

17. The computer implemented method of claim 11 , wherein obtaining seasonal data that includes geolocated seasonal values of the agricultural characteristics corresponding to a current season comprises one or more of:

obtaining seasonal crop planting data that includes geolocated seasonal crop planting values corresponding to the current season;

obtaining seasonal weather data that includes geolocated seasonal weather values corresponding to the current season; or

obtaining seasonal crop development data that includes geolocated seasonal crop development values corresponding to the current season.

18. The computer implemented method of claim 11 , wherein controlling a controllable subsystem comprises at least one of:

generating a header control signal based on the detected geographic location of the agricultural work machine and the functional predictive crop state map and controlling the controllable subsystem based on the header control signal to control a header actuator of the agricultural work machine;

generating a speed control signal based on the detected geographic location and the functional predictive crop state map and controlling the controllable subsystem based on the speed control signal to control a speed of the agricultural work machine;

generating a path planning control signal, indicative of a route, based on the detected geographic location of the agricultural work machine and the functional predictive crop state map and controlling the controllable subsystem based on the route; or

generating an operator interface control signal and controlling the controllable subsystem to generate a user interface map representation of the functional predictive crop state map.

19. An agricultural system comprising:

a communication system configured to obtain:

historical crop state data indicative of historical values of crop state;

historical agricultural characteristics data indicative of historical values of agricultural characteristics; and

seasonal data indicative of geolocated seasonal values of the agricultural characteristics corresponding to a current season; and

a predictive model generator configured to generate a historical predictive crop state model that models a relationship between the historical values of crop state and the historical values of the agricultural characteristics;

a predictive map generator configured to generate a predictive crop state map of a field that maps predictive crop state values to different geographic locations in the field based on the seasonal values of the agricultural characteristics in the seasonal data at those different geographic locations and the historical predictive crop state model;

a geographic position sensor configured to detect geographic locations of an agricultural work machine; and

a control system that generates a control signal to control a controllable subsystem of the agricultural work machine based on a detected geographic location of the agricultural work machine and based on a predictive crop state value in the predictive crop state map.

20. The agricultural system of claim 19 and further comprising:

an in-situ sensor configured to detect a value of crop state corresponding to a geographic location in the field; and

wherein the predictive model generator is configured to generate a revised historical predictive crop state model that models a relationship between crop state values, which include the value of crop state and the historical values of crop state, and agricultural characteristics values, which include the historical values of the agricultural characteristics and the seasonal values of the agricultural characteristics corresponding to the geographic location of the value of crop state;

wherein the predictive map generator is configured to generate a revised functional predictive crop state map that maps revised predictive crop state values to different geographic locations in the field based on seasonal values of the agricultural characteristics corresponding to the different geographic locations and the revised historical predictive crop state model; and

wherein the control system generates an additional control signal to control the controllable subsystem based on an additional detected geographic location of the agricultural work machine and based on a revised predictive crop state value in the revised functional predictive crop state map.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 1, 2021
From: ANDERSON, NOEL W.; HEIEN, ERIC M.; VANDIKE, NATHAN R.
To: DEERE & COMPANY
Reel/Frame 057668/0101 →
Continuity (1)
Related Publication 20230107444A1 · Apr 6, 2023
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